Do I need to denormalise results in linear regression?
Okay, I figured it out by myself, simply by trial and error:

When you normalize your training and test data, you also need to normalize the input you want to have a prediction for. You will also need to denormalize the result, to get a reasonable prediction.

Specifically, in my case, this means:


First I calculated the mean and the standard deviation, and then subtracted the mean and divided by standard deviation, to normalize my training and test data.
So to normalize the input I want to have a prediction for, I also subtract the mean and divide by the standard deviation.
Finally, when I get a result, I multiple by the standard deviation, and add the mean.


This way, I get reasonable results